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Exploring the Effectiveness of Socially-Oriented Persuasive Strategies in Education

  • Fidelia A. Orji
  • Jim GreerEmail author
  • Julita VassilevaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11433)

Abstract

Persuasive technology (PT) has been shown to be effective at motivating people to accomplish their behaviour goals in different areas, especially health. It can support students to improve their learning by increasing their motivation to engage deeply with their educational resources. Research on the use of persuasive systems to improve students’ motivation to learn is still scarce. Thus, in this research, we examined whether three socially-oriented influence strategies (upward social comparison, social learning, and competition), implemented in a persuasive system, can motivate students to engage more in learning activities. Research has shown that the strategies can motivate people for attitude- or behaviour-change when employed in PT design. The strategies were operationalized in a persuasive system as three versions of visualization using students’ assessment grades. The persuasive system was applied in a real university setting to determine whether it can encourage students to improve their learning activities in an introductory biology class. Three groups of students used the persuasive system versions, each group used one version. Among the groups, some students received a version of the persuasive system, tailored to their personal preference to the corresponding influence strategy. The results of this research analysis show that tailoring the persuasive system versions to students’ strategy preference increases its effectiveness. Moreover, the results reveal that the three social influence strategies can be employed in educational software to influence students to achieve a positive goal in their learning.

Keywords

Persuasive technology Social influence Persuasion profile Personalization Social comparison Social learning Competition Education 

Notes

Acknowledgement

This work has been supported by the NSERC Discovery Grant of the third author.

References

  1. 1.
    Bandura, A.: Social learning theory. Gen. Learn. Corp. 1971, 1–46 (1971)Google Scholar
  2. 2.
    Busch, M., Schrammel, J., Tscheligi, M.: Personalized persuasive technology – development and validation of scales for measuring persuadability. In: Berkovsky, S., Freyne, J. (eds.) PERSUASIVE 2013. LNCS, vol. 7822, pp. 33–38. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-37157-8_6CrossRefGoogle Scholar
  3. 3.
    Christy, K.R., Fox, J.: Leaderboards in a virtual classroom: a test of stereotype threat and social comparison explanations for women’s math performance. Comput. Educ. 78, 66–77 (2014)CrossRefGoogle Scholar
  4. 4.
    Dijkstra, P., Kuyper, H., Van der Werf, G., Buunk, A.P., van der Zee, Y.G.: Social comparison in the classroom: a review. Rev. Educ. Res. 78(4), 828–879 (2008)CrossRefGoogle Scholar
  5. 5.
    Fogg, B.J.: Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann Publishers, ‎Burlington (2002)Google Scholar
  6. 6.
    Kaptein, M.: Adaptive persuasive messages in an e-commerce setting: the use of persuasion profiles. In: European Conference on Information Systems (ECIS), p. 183 (2011)Google Scholar
  7. 7.
    Kaptein, M., De Ruyter, B., Markopoulos, P., Aarts, E.: Adaptive persuasive systems: a study of tailored persuasive text messages to reduce snacking. ACM Trans. Interact. Intell. Syst. 2(2), 1–25 (2012)CrossRefGoogle Scholar
  8. 8.
    Kupek, E.: Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders. BMC Med. Res. Methodol. 6(1), 13 (2006)CrossRefGoogle Scholar
  9. 9.
    Oinas-Kukkonen, H., Harjumaa, M.: Persuasive systems design: key issues, process model and system features. Commun. Assoc. Inf. Syst. 24, 485–500 (2009)Google Scholar
  10. 10.
    Orji, R., Mandryk, R.L., Vassileva, J.: Improving the efficacy of games for change using personalization models. ACM Trans. Comput.-Hum. Interact. 24(5), 1–22 (2017)CrossRefGoogle Scholar
  11. 11.
    Orji, R., Vassileva, J., Mandryk, R.L.: Modeling the efficacy of persuasive strategies for different gamer types in serious games for health. User Model. User-Adapt. Interact. 24(5), 453–498 (2014)CrossRefGoogle Scholar
  12. 12.
    Orji, R., Oyibo, K., Lomotey, R.K., Orji, F.A.: Socially-driven persuasive health intervention design: competition, social comparison, and cooperation. Health Inform. J. (2018).  https://doi.org/10.1177/1460458218766570
  13. 13.
    Orji, R., Nacke, L.E., Di Marco, C.: Towards personality-driven persuasive health games and gamified systems. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI 2017, New York, USA, pp. 1015–1027 (2017)Google Scholar
  14. 14.
    Orji, R., Moffatt, K.: Persuasive technology for health and wellness: state-of-the-art and emerging trends. Health Inform. J. 24(1), 66–91 (2018)CrossRefGoogle Scholar
  15. 15.
    Social influence theory (2000). https://is.theorizeit.org/wiki/Social_Influence_Theory. Accessed 04 July 2018
  16. 16.
    Stibe, A., Oinas-Kukkonen, H.: Using social influence for motivating customers to generate and share feedback. In: Spagnolli, A., Chittaro, L., Gamberini, L. (eds.) PERSUASIVE 2014. LNCS, vol. 8462, pp. 224–235. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-07127-5_19CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of SaskatchewanSaskatoonCanada

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